Soft computing, as a collection of techniques exploiting
approximation and tolerance for imprecision and uncertainty in
traditionally intractable problems, has become very effective and
popular especially because of the synergy derived from its
components. The integration of constituent technologies provides
complementary methods that allow developing flexible computing
tools and solving complex problems. A wide area of natural
applications of soft computing techniques consists of the control
of dynamic systems, including robots. Loosely speaking, control can
be understood as driving a process to attain a desired goal.
Intelligent control can be seen as an extension of this concept, to
include autonomous human-like interactions of a machine with the
environment. Intelligent robots can be characterized by the ability
to operate in an uncertain, changing environment with the help of
appropriate sensing. They have the power to autonomously plan and
execute motion sequences to achieve a goal specified by a human
user without detailed instructions. In this volume leading
specialists address various theoretical and practical aspects in
soft computing, intelligent robotics and control. The problems
discussed are taken from fuzzy systems, neural networks,
interactive evolutionary computation, intelligent mobile robotics,
and intelligent control of linear and nonlinear dynamic
systems.
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